MVP READY · PILOT INTEGRATIONS OPEN

The Intelligence And Trust Layer
For Autonomous AI Agents

Your agents are ready. The infrastructure to trust them at scale isn't.
Trellar is the layer that closes that gap.

0%
of enterprises have adopted AI agents
0%
actually run them in production
0%
of proofs-of-concept never ship

The gap isn't capability. It's the absence of trust infrastructure.

The Framework

See. Control. Trust. Unleash.

Each step is only possible because of the one before it. Trellar is the operational infrastructure that makes the sequence work.

01

See

Full visibility into what every agent in your network is doing at runtime.

02

Control

Enforce what each agent is and isn't allowed to do at runtime.

03

Trust

Confidence the system behaves as intended, backed by evidence.

04

Unleash

Extend autonomy further, because now you have the ground truth to.

The Problem

Trust doesn't scale the way your agents do.

Platform teams running multi-agent systems in production already have observability. Logs, traces, exports, dashboards. What they don't have is a way to prove any given agent is safe enough to run with less oversight than it gets today, or a way to govern that isn't gated behind whoever on the team is technical enough to build it.

So autonomy stays throttled, not for lack of capability but for lack of a systematic way to build trust and a systematic way for every team, technical or not, to act on it.

The workaround most teams build is a patchwork of monitoring exports, custom scripts, periodic manual reviews, and hard limits on what agents are allowed to do, usually owned by whichever team has the engineering resources to build it. It prevents catastrophic failure. It doesn't build trust, and it doesn't scale past the team that built it.

The Difference

Most governance tools make agents safer by making them weaker.

Security and control plane tools restrict what agents can accomplish. That reduces risk, but it reduces capability at the same rate, which is the opposite of what teams running multi-agent systems actually need.

Trellar takes a different approach. It defines what each agent is authorized to do and monitors every run against that definition, so agents operate at full capacity within their boundaries instead of being boxed in by default. Trust is built from evidence, real runtime behavior, not assumptions, so when you're ready to extend autonomy, you have the ground truth to justify it.

Trust shouldn't depend on how technical your team is. Every team governs its own agents, in plain language, within its own scope, instead of waiting on whoever owns the tooling.

Think of it like onboarding a new hire. Close supervision early, easing off as trust is earned, with certain boundaries that never relax. The goal isn't permanent oversight. It's earning the right to reduce it.

Capabilities

Everything you need to govern agents in production

Sits above any agent framework your team is already running. No replacement, no migration.

Performance Intelligence

Behavioral baselines per agent. Health scores, latency rankings, and anomaly detection that fires before an incident.

Drift Detection

Workflow Observability

A full, searchable timeline of every run, tool call, decision point, and LLM call, so you can trace an issue back to where it started.

Real-Time Tracing

Policy Enforcement

Runtime control over what agents can do. Write rules directly, or upload policy docs and let Trellar translate them. Risk tolerance is yours to set.

Runtime Guards

Human Escalation

Pauses agents at defined decision points, routes to the right person with full context, and resumes on approval. Escalation follows your team's structure, so it never becomes a bottleneck.

Smart Routing

Training Force

Feeds evaluations and escalation decisions back into the model, so behavior improves over time and human intervention drops as trust builds.

Auto-Improvement

Agentic Network Analysis

Query your entire agent network in plain language. See every agent, tool, and handoff mapped, and turn root-cause analysis into a conversation with the system instead of a manual dig through logs.

Natural Language Query
Built For Every Team

AI governance shouldn't require engineering to run.

Governance has always defaulted to whoever has the most technical resources, which means everyone else waits. Compliance waiting on engineering for policy changes. Business owners waiting on platform teams to know what their agents are doing. Governance as a bottleneck instead of a foundation.

Trellar is built so every team governs its own agents, in its own scope, without depending on anyone else to translate for them. Write policy in plain language and Trellar enforces it. Set risk tolerance and escalation routing through the interface. Every new agent inherits a baseline of oversight the moment it connects, so no team starts from zero.

When everyone can act within their own scope, governance stops being a bottleneck and starts being an accelerator.

Works on top of the frameworks your team already runs

Trellar sits above your existing stack. No replacement, no migration, no changes to your orchestration code. If your agents are already running, Trellar activates on the first run.

Setup

Activate in minutes, not days

No configuration sprint. No integration project. Trellar sits above your existing stack and starts delivering value on the first run.

01

Connect your stack

Works above any framework you're already running

02

First run, first value

Baselines and evaluations build themselves automatically

03

Extend with confidence

See, control, and trust your agents from day one

Trellar operates outside your execution path, so there's no latency added to agent output and nothing to migrate or reconfigure in your existing stack.

Who It's For

Built for the teams who own agents in production

Engineers

Building and owning orchestration pipelines who need to see what agents are doing at runtime and debug failures without reconstructing runs from incomplete logs.

Platform & Ops Leads

Who get asked "what happens when it fails?" and are tired of answering from exports and manual spot-checks they don't fully trust.

CISOs & Compliance Leads

Accountable for what agents do in production, who need documented human oversight, audit trails, and enforcement records.

CTOs & VPs of Engineering

Watching working prototypes stall before production, needing the governance infrastructure to get them across the line.

Business Owners & Team Leads

Running agents that touch your workflows, but dependent on engineering to explain what they're doing and set the rules. Trellar gives you a direct view and direct controls, no technical translation required.

Why Now

You already did the hard part.

Building a multi-agent network was the heavy lift. Most of the value you built into it is still sitting on the table, held back by how much you can trust it to run on its own.

Extending autonomy is what turns that investment into ROI. Every task an agent can safely handle without a human in the loop is time and cost the network is already capable of saving. Trellar is what makes it safe to let that happen.

Early Access

Request early access to Trellar

MVP is ready. We're selecting a small group of pilot partners. Tell us about your setup and we'll reach out within 3 business days.

23 of 50 early access seats still available

We review every request personally. You'll hear back within 3 business days.